仓库/Skill 库

开源、原生支持 Claude 的文献综述工作流工具：支持 arXiv/DOI/URL/PDF 论文导入、章节抽取，并通过 paper-qa 实现单篇论文问答Open-source, Claude-native literature-review workflow tool: arXiv/DOI/URL/PDF paper ingest, section extraction, single-paper Q&A via paper-qa.

本项目根据用户检索与数据集中已有论文进行论文推荐This project recommends paper based upon your search and available papers inside the dataset

智能研究论文推荐系统，聚合 ArXiv 与 Semantic Scholar 内容，简化学术发现流程。An intelligent research paper recommender system aggregating content from ArXiv and Semantic Scholar to streamline academic discovery.

Download consensus ai，可在数秒内从科学论文中获取有证据支撑的答案。面向学生、临床工作者与好奇读者，Consensus 将复杂研究转化为清晰、带引用的洞察，是值得信赖的共识研究工具，助力更快文献综述与更明智决策。Download consensus ai to find evidence-backed answers from scientific papers in seconds. Built for students, clinicians, and curious readers, Consensus turns complex studies into clear insights with citations, making it a trusted consensus research tool for faster literature review and smarter decisions.

全球研究者的终极 AI 驱动发现平台。统一搜索 8+ 专业数据库（NCBI、arXiv、OpenAlex），结合 Llama 3.1 驱动的综合分析、RAG 问答与自动化文献综述。The ultimate AI-powered discovery hub for global researchers. Unified search across 8+ specialized portals (NCBI, arXiv, OpenAlex) with Llama 3.1-driven synthesis, RAG chat, and automated literature reviews.

综述论文《From Representation Learning to Foundation Models》的官方仓库。系统综述空间转录组学与病理学的多模态融合，提出三层分类法（Embedding、Model、Knowledge 层级）及 2018 至 2025 的演进路线图。Official repository for the survey "From Representation Learning to Foundation Models". A systematic review of multimodal fusion for Spatial Transcriptomics and Pathology, featuring a three-tier taxonomy (Embedding, Model, and Knowledge levels) and an evolutionary roadmap from 2018 to 2025.

面向文献综述与历史学期刊策略的合规本地优先 Codex Skills。Rights-safe local-first Codex Skills for literature review and history journal strategy.

可审计的按需学术文献综述引擎Auditable on-demand academic literature review engine

Fintool 是一款面向对冲基金、资管机构及买方/卖方分析师等机构投资者的 AI 驱动股票研究分析师与金融副驾驶。其助手可摄取 SEC 文件（10-K、10-Q、8-K）、财报电话会议记录与金融数据，并附带来源引用地回答研究问题，加速……Fintool is an AI-powered equity research analyst and financial copilot built for institutional investors such as hedge funds, asset managers, and buy-side and sell-side analysts. Its assistant ingests SEC filings (10-K, 10-Q, 8-K), earnings-call transcripts, and financial data to answer research questions with source citations, accelerating…

基于个人研究兴趣的每日 arxiv 论文推荐，由 Claude 更新。Daily arxiv paper recommendation based on my research interest, updated by Claude.

Claude Code Skill，可将论文与对话转化为交叉链接的 Obsidian 知识库：十段式论文笔记含内嵌图表，归档于主题枢纽下Claude Code skills that turn papers and conversations into a cross-linked Obsidian knowledge base — ten-section paper notes with inline figures, filed under topic hubs.

LLM 驱动的科学论文推荐系统LLM-driven scientific paper recommendation system

一个基于 C# 与本地 LLM 的学术论文 RAG（Retrieval-Augmented Generation）系统。目标是摄入研究论文语料，构建可回答文献综述类问题（如"其他论文关于 X 发现了什么"）的系统，回答严格基于真实源材料。A RAG (Retrieval-Augmented Generation) system for academic papers using C# and a local LLM. The goal is to ingest a corpus of research papers and build a system that can answer literature review questions like "what have other papers found about X"; grounded in the actual source material.

本仓库为关于肌少症 AI 驱动体形分析动态文献综述的源代码。通过自行修改配置文件，本仓库也可作为其他领域的模板使用。Store here are the source code for the dynamic Literature Review on AI-Driven Body Shape Analysis for Sarcopenia. You may also treat this repository as a template for other domains by configuring the configuration files by yourself.

提出研究问题，获得可核验的带引文报告Ask a research question, get a cited report you can check.

OncoRAG 是一个 RAG 系统，为临床医生和研究人员提供即时获取最新肿瘤学证据的能力——来源包括直接来自 PubMed 的随机对照试验、Meta 分析、系统综述和 III 期临床试验。提出临床问题，即可获得带引文的可靠答案。OncoRAG is a Retrieval-Augmented Generation system that gives clinicians and researchers instant access to the latest oncology evidence — drawing from Randomized Controlled Trials, Meta-Analyses, Systematic Reviews, and Phase III Clinical Trials sourced directly from PubMed. Ask a clinical question, get a grounded answer with citations.

基于内容相似度的机器学习论文推荐系统，使用 Python 与自然语言处理技术。Machine learning recommendation system that suggests relevant research papers based on content similarity using Python and natural language processing techniques.

学术论文推荐系统research paper recommendation system

学术论文推荐系统research paper recommendation sysytem